# MRI Brain Tumor Analysis on Improved VGG-16 and Efficient NetB7 Models

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/mri-brain-tumor-analysis-on-improved-vgg-16-and-efficient-netb7-models/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Salini Yalamanchili,Padma Yenuga,Nagaraju Burla,Harikiran Jonnadula,Sai Chandana Bolem,Venkata Rami Reddy Chirra,Venkata Ramana M,Parimala Garnepudi,Narasimha Rao Yamarthi |
| Citations | 6 |
| DOI | 10.18178/joig.12.1.103-116 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://doi.org/10.18178/joig.12.1.103-116 |
| OpenAlex ID | https://openalex.org/W4395096409 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Venkata Rami Reddy Chirra](https://scholariq.org/researchers/venkata-rami-reddy-chirra/)

## Paper journal

- [Journal of Image and Graphics](https://scholariq.org/journals/journal-of-image-and-graphics/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Medical Imaging Techniques and Applications](https://scholariq.org/topics/medical-imaging-techniques-and-applications/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.